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Agentbaseret Scenarieanalyse×Monte Carlo-simulering×
FagområdeSimuleringBeslutningstagning
FamilieProcess / pipelineMCDM
Oprindelsesår1990s–2000s1949
OphavspersonAxelrod, R.; Schoemaker, P. J. H. (combined lineage)Metropolis, N., Ulam, S.
TypeHybrid simulation–scenario methodRobustness wrapper — Monte Carlo uncertainty propagation
Oprindelig kildeAxelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. Princeton, NJ. ISBN: 9780691015675Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
AliasserABSA, ABM scenario analysis, agent-based scenario planning, scenario-driven ABM
Relaterede40
ResuméAgent-based scenario analysis embeds agent-based simulation models inside a structured scenario planning framework. Researchers define two to four contrasting future scenarios, configure agent populations and environmental rules to reflect each scenario's assumptions, run the simulation under each condition, and compare emergent outcomes. This makes it possible to explore how decentralized individual behaviors aggregate into system-level consequences under radically different futures.MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateSammenlign metoder: Agent-based scenario analysis · MONTE-CARLO-SIMULATION. Hentet 2026-06-17 fra https://scholargate.app/da/compare